Data Science Sunday Episode 36, 2024
Statistics accounts for uncertainties, putting a figure to uncertainties
— Peter Okwukogu
Thanks to Everyone at Colab kaduna Data Science Sundays, and most especially the convener Sanusi, and the facilitator Peter Okwukogu.
It was a moment where we had Data scientists from across the globe, from Africa, Asia, South America etc. all in one call.
This was the 36th meeting for individuals interested in learning more about Python from scratch, grasping key Data Science, and Data Analysis Concepts.
We engaged in Hands-on Coding Exercises, Participated in Q&A Sessions, and Networked with like-minded individuals.
We were taken through Jupyter Notebook.
We went through Python Docs and Glossary.
We were given links to resources on Data Science, Statistics, Anaconda, and Python Basics on YouTube, and Links to previous episodes.
This was a question-and-answer-filled session.
We worked on explaining inner joins in Pythons’ data frames.
Explaining Inner Joins
# Merge two dataframes
# Common features
# Combining two records from two tables with a common value(Match)
# Matching values
# Exclude rows from both tables without matching values
# Practical Example: Two datasets
# A customer data frame -
Pandas data frame
# An orders data frame - Pandas data frame
# import packages
import pandas as pd# The customer's data frame
data_customers = {'CustomerID': [1,2,3,4],
'CustomerName': ['Oyeshina', 'Collins', 'Elizabeth', 'Pablo"]}
print (data_customers)
('CustomerID': [1, 2, 3, 4], 'CustomerName': ['Oyeshina', 'Collins', 'Elizabeth', 'Pablo']}
# Use the dictionary to create a data frame pd. DataFrame (data_customers)# Create the orders data frame
data_orders = {'OrderID': [101, 102, 103, 104),
'CustomerID': [2,3,5,1],
'OrderAmount': [250,150,175,200]}
orders = pd. DataFrame (data_orders)
orders# Operation merge
# customers & orders
merge_df = pd.merge(customers, orders, on='CustomerID', how='inner")merge_df
Other questions asked during the meeting :
Question : Good evening. I wanted to know if there are alternative links to installing Anaconda because the installation using the latest installer available keeps failing on a Windows 7 system. I am trying to avoid having to do an OS install.
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Question : Hello good evening Mr Pablo
I am new here and actually new to computers. Please I need your advice on how and where should I start from (especially data science and coding).
My takeaway from this meeting :
- We can combine records from two tables with common values
- We can exclude rows from two tables that don’t have matching values.
Useful Links:
https://thewhistler.ng/economists-explain-how-the-dollar-affects-food-prices-in-nigeria/
https://www.economist.com/middle-east-and-africa/2024/07/11/soaring-food-price-inflation-is-hurting-nigerias-poor
https://agrifoodnetworks.org/article/unraveling-nigerias-food-crisis
https://www.cbc.ca/news/world/us-debt-crisis-global-impact-1.6852085
https://money.usnews.com/investing/articles/de-dollarization-what-happens-if-the-dollar-loses-reserve-status
https://theconversation.com/why-economists-are-warning-of-another-us-banking-crisis-224092
https://edition.cnn.com/2023/03/19/economy/central-banks-fed-dollar-liquidity/index.html
https://machinelearningmastery.com/make-predictions-scikit-learn/
https://neo4j.com/blog/build-predictive-model-python/
https://learnsql.com/blog/sql-joins-complete-guide/
https://realpython.com/python-ai-neural-network/
https://machinelearningmastery.com/make-predictions-time-series-forecasting-python/
https://builtin.com/data-science/time-series-forecasting-python
https://cb-nigeria.opendataforafrica.org/
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